-
GPUMD
stands for Graphics Processing Units Molecular Dynamics. It is a general-purpose molecular dynamics (MD) code fully implemented on graphics processing units (GPUs). -
Force evaluation for many-body potentials has been significantly accelerated by using GPUs [1], thanks to a set of simple expressions for force, virial stress, and heat current derived in Ref. [2].
-
Apart from being highly efficient, another unique feature of GPUMD is that it has useful utilities to study heat transport [3, 4].
- You need to have a GPU card with compute capability no less than 3.5 and a
CUDA
toolkit no older thanCUDA
9.0. - Works for both Linux (with GCC) and Windows (with MSVC) operating systems.
- Go to the
src
directory and typemake
. When the compilation finishes, two executables,gpumd
andphonon
, will be generated in thesrc
directory.
- Go to the directory where you can see
src
. - Type
src/gpumd < examples/input_gpumd.txt
to run the examples inexamples/gpumd
. - Type
src/phonon < examples/input_phonon.txt
to run the examples inexamples/phonon
.
- We only maintain the online manual now: https://gpumd.zheyongfan.org
-
You can use the following link to subscribe and unsubscribe the mailing list: https://www.freelists.org/list/gpumd
-
To post a question, you can send an email to gpumd(at)freelists.org
-
Here is the archive (public): https://www.freelists.org/archive/gpumd/
- One of the developers, Alexander J. Gabourie, has written a Python package for pre-processing and post-processing data related to
GPUMD
. Here is the link: https://github.com/AlexGabourie/thermo
- Zheyong Fan (Bohai University and Aalto University; Active developer)
- brucenju(at)gmail.com
- Alexander J. Gabourie (Stanford University; Active developer)
- gabourie(at)stanford.edu
- Ville Vierimaa (Aalto University; Not an active developer any more)
- Mikko Ervasti (Aalto University; Not an active developer any more)
- Ari Harju (Aalto University; Not an active developer any more)
- If you use
GPUMD
in your published work, we kindly ask you to cite the following paper which describes the central algorithms used inGPUMD
:
[1] Zheyong Fan, Wei Chen, Ville Vierimaa, and Ari Harju. Efficient molecular dynamics simulations with many-body potentials on graphics processing units. Computer Physics Communications 218, 10 (2017). https://doi.org/10.1016/j.cpc.2017.05.003
- If you want to cite a link to the GPUMD code you can cite the current Github page: https://github.com/brucefan1983/GPUMD.
- However, if the journal does not accept this citation, you can check the Zenodo page of GPUMD (https://zenodo.org/record/4037256#.X2jkqWj7SUk) and cite the version you used. Each version has a unique DOI, which is very suitable for citation. Remember to change the author list to Zheyong Fan and Alexander J. Gabourie.
- If your work involves using heat current and virial stress formulas as implemented in
GPUMD
, the following paper can be cited:
[2] Zheyong Fan, Luiz Felipe C. Pereira, Hui-Qiong Wang, Jin-Cheng Zheng, Davide Donadio, and Ari Harju. Force and heat current formulas for many-body potentials in molecular dynamics simulations with applications to thermal conductivity calculations. Phys. Rev. B 92, 094301, (2015). https://doi.org/10.1103/PhysRevB.92.094301
- You can cite the following paper if you use
GPUMD
to study heat transport using the in-out decomposition for 2D materials and/or the spectral decomposition method as described in it:
[3] Zheyong Fan, Luiz Felipe C. Pereira, Petri Hirvonen, Mikko M. Ervasti, Ken R. Elder, Davide Donadio, Tapio Ala-Nissila, and Ari Harju. Thermal conductivity decomposition in two-dimensional materials: Application to graphene. Phys. Rev. B 95, 144309, (2017). https://doi.org/10.1103/PhysRevB.95.144309
- You can cite the following paper if you use
GPUMD
to study heat transport using the HNEMD method and the associated spectral decomposition method:
[4] Z. Fan, H. Dong, A. Harju, T. Ala-Nissila, Homogeneous nonequilibrium molecular dynamics method for heat transport and spectral decomposition with many-body potentials, Phys. Rev. B 99, 064308 (2019). https://doi.org/10.1103/PhysRevB.99.064308